We introduce \((\varepsilon , \delta )\) -bisimulation, a novel type of approximate probabilistic bisimulation for continuous-time Markov chains. In contrast to related notions, \((\varepsilon , \delta )\) -bisimulation allows the use of different tolerances for the transition probabilities ( \(\varepsilon \) , additive) and total exit rates ( \(\delta \) , multiplicative) of states. Fundamental properties of the notion, as well as bounds on the absolute difference of time- and reward-bounded reachability probabilities for \((\varepsilon ,\delta )\) -bisimilar states, are established.